With IT Revolution, user generated contents can be easily posted online. The total volume and the rapid growth of this information provide possible value to business, government and user themselves. Moreover, many customer-promoted reviews of products and services have become extremely useful resources for market analysis. These reviews are used to set business strategies for popular websites such as Amazon.com and Epinion.com. Online users also gain advantage from reading others opinions.
There is an essential property called Sentiment involved in the huge majority of online-created contents. Sentiment is an opinion, point of view or attitude you have about something. Sentiment Analysis expressing enthusiast using natural language processing. It is also defined as the process of computationally identifying and categorizing opinions expressed in a piece of text, especially in order to determine whether the writer's attitude towards a particular topic, product, etc. is positive, negative, or neutral.
Generally speaking, the main aim is to determine the attitude of the speaker with respect to specific topic. The attitude may be his own judgment or evaluation. The focus is to identify the sentiment polarity of given context, whether it is classified as positive or negative. Analyzing and anticipating the polarity of the sentiment plays a crucial role in understanding the social phenomena and general society trends.
Nowadays, sentiment classification has become a very popular research topic. The sentiment classification problem was initially handled at levels of document, word, phrases depending on specific goals of the applications .It is not just a topic but deals with computational treatment of belief, idea and subjectivity in text. It is beneficial in recommendation system and question answering.PREVIOUS NEXT
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